An Interview with Dani, Scientific Agitator

The newest part of our blog series ‘An Interview with …’ asks Dani, scientific agitator through art and immersive experiences, about his work, PhD research and experience of learning about data and technology

Working with data and technology can be difficult and overwhelming for a lot of people. So, we at Taught By Humans are running a series of interviews with professionals to help demystify these topics for you. How are data and technology useful and/or significant within different roles? How do people learn about data and technology and their applications? How can we keep our knowledge of data and technology up to date? Our interviewees will be helping us to answer these questions and more.

Our newest interviewee is Dani, scientific agitator through art and immersive experiences. He answered a few questions for us relating specifically to his experience of working with data and technology, his PhD research and perspective on methods of learning.

The Interview

Okay, so can you start by giving a bit of a background into who you are and what you do?

Sure. I call myself a scientific agitator. That’s a role I created, and it means that I try to create a connection between researchers and society through the arts and creative experiences. I called this scientific agitation, so I am a scientific agitator. And this comes from my PhD in robotics, which I did at the Bristol Robotics Lab. There, I did swarm robotics, which is an increasingly important topic. In robotics, we try to take inspiration from nature, such as swarms of animals, to design our multiple robot solutions. And before that, I studied computer science. That’s what got me into into robotics. I wanted to create technology that could be useful for society. So I decided to do a PhD. And then in a PhD, I realised of the importance of science communication and public engagement.

Why did you decide to work in scientific agitation specifically? What is it and why is it important?

I decided to work in scientific agitation by the middle of my PhD. I remember, at the beginning, I wanted to help firefighters, because when I was studying computer science, I had to face a fire at my neighbour’s house. It was a dramatic situation but luckily no one was injured. My neighbour called me to her apartment because there was an old lady inside the bathroom, and the radiator above the door of the bathroom had caught fire. So it was a pretty dangerous, scary situation. We took her out, and we called emergency services. And from that experience, I knew I wanted to help firefighters because I had seen myself how dangerous it is for them to do this every day. So, I started my PhD with that in mind. I started using my robot to properly design a swarm that could enter into a building on fire and find the people who needed to be rescued, rescue them, put out that fire and do everything by themselves. In my mind, I thought that was super cool and super useful. But, I didn’t consider asking firefighters themselves if that was something they wanted, and by the middle of my PhD, I received training in Responsible Research and Innovation through a European project called Perform. And that was nice because they trained early career researchers like me in science communication. Through this I realised I should ask firefighters because maybe I’m not growing or developing the right technology. I decided to do that through the arts and creative experiences, because I could see that I could create a more fruitful connection that way. So, I designed a few focus groups with them, where I also included a bit of a demo of my robots, so they could actually see what the technology is about, and have a conversation. And that was super nice, because we had a two way conversation where I could also learn their hopes and fears, what they want, and what they don’t really need. And through that, for example, I learned that they don’t want robots to do everything. They specifically want robot swarms to do information gathering tasks, like creating a map for them, like finding those casualties or identifying hazards, so that they could go directly to where where the people are and rescue them, but minimise the risk.

What have you learned through that role about what motivates people? And how do you think we can use this understanding to motivate learning in data and technology?

I think one of the main lessons I have learned is that people want to be included in the development of technology. That’s something firefighters expressed themselves. I handed over some questionnaires at the beginning and the end of the focus groups, and the last question was about if and when they wanted to be included in the research and development process. Three quarters of them said that they wanted to be included from the beginning, from the early stages. That was a very important finding, which also continued to be true when I engaged the general public. Later in my project, I also designed an escape room to tell the general public about my research in swarm robotics, and how it could eventually affect them. Because then they won’t be surprised if a bunch of robots ever appears when they are in the middle of a building on fire! That will eventually, hopefully, become a reality. So, people need to know beforehand. I organised another discussion session with the people who came, and it was great to see the level of involvement in such discussions. We sat down with them and asked them, for example, what kind of applications they see robot swarms doing. And they came up with such a massive amount of applications, which they then put in a benefits versus risks graph. We stuck on it on the walls, and it was super nice to see that people can have a say, and need to have a say on these conversations. So, I would say that that’s the main finding: that people want to be part of the conversation in the development of technology.

You also work with RoboHub. Can you explain a bit about what they do, and what your role with them looks like?

Sure. So RoboHub are a nonprofit, educational platform, and we try to connect the robotics community with the rest of the world. We do this mainly through our blog and our podcast, where we try to give voice to roboticists from all over the world, from any background, gender, race, etc. For RoboHub, I am the managing editor. That means I make sure that the content we publish is truthful, fair, and balanced. When I receive articles from people, I also make sure it’s high quality, and that we adapt to the language that the general public is used to. We try to avoid high academic language, although sometimes it’s cool to have some articles like that so that people can have a chance to see what it looks like. And apart from that, we are also launching sitecom.io which is a new project now between RoboHub and AI Hub, which is the partner project more focused on AI and these cycles, who will be an educational platform where we will train the next generation of science communicators in robotics and AI. And for that project, I am one of the lead trainers. So, I will be facilitating training courses and science communication, focused more on general science communication and the different ways to do it. This will be linked more to my expertise on thinking out of the box and using the arts and creative experiences.

What are your thoughts about how we can connect the robotics community with the general public and make complex topics like this more accessible?

I think we have to speak the same language. And by that I mean to adapt to the formats that people are used to. That’s how I realised that using the arts and the more immersive experiences could help engage society into a conversation. For example, I designed an educational escape room about swarm robotics because pretty much everyone loves escape rooms and games. So, I decided that I couldn’t wait to engage society in a conversation through a game, and afterwards people were wanting to have a chat about the technology that was shown in the escape room: swarm robotics. They had that excitement from the game to actually start a conversation on the topic. So, I think we have to find the people and adapt to what they are used to rather than the other way around.

In either of your roles, how do you use and work with data and technology to make your job easier?

For RoboHub, we mainly use our website. And for that, we use WordPress, which is a super easy and simple way to build your own website. So that enormously facilitates our job, because we perceive the articles, maybe we subscribe to other robotics magazines or blogs, and we automatically receive what they post. If we receive a custom article from, say, researchers by email, it’s super easy to put that into the website. So WordPress is a technology that facilitates our lives a lot. And, for my role in scientific agitation, I like to collect people’s opinions to analyse the data, find patterns and identify what’s being said across the group. For that, that process facilitates me a lot, because it’s a way to make more general claims. It’s always important to include what every person says, but by collecting them all together and grouping the information, we can identify those patterns and be more confident that the results we get could be generalised.

How did you learn to do all of that? And is your learning process one that you would recommend others use?

I learned that from my PhD. But I don’t think you have to enrol in a PhD to learn it! I always recommend people do a PhD because it’s a process of personal and professional development. But you don’t have to do big data to go through that process and to learn those skills. As part of a PhD or not, learning is all about and all starts with questions. For example, a question that comes to mind is, ‘how can I make sure that my plants, when I am away, will be well watered, especially if my neighbours are also holidays?’ That could be a research question where you don’t have to do a PhD, but you can learn a lot of new skills like how to do scientific experiments, how to set up your own experiments, how to analyse the results through finding an answer. Say you put different plants on different watering systems, and then later when you come back from your holidays, you can analyse the data. That would be a good learning process. Through my PhD, I also learned that it’s always good to look for advice from the experts. And then, I learned by myself through trial and error. So, learning can be done through a combination of those things, and you can do that at home without doing a PhD. Either way, it all starts with a question and following your motivation to find the answer.

Is there any other information or advice you’d like to share with those who aren’t confident or are looking to learn more about data and technology?

I would say, and I always encourage people, to ask for a place in the conversation if they feel their thoughts could be taken into account. By that I mean it’s always good to be part of the development of technology and have a voice on that, because it will eventually affect us all, individually and as a society. So, if we are part of the conversation, then we can try to make sure that our opinions are taken into account. If people don’t feel they’re being taken into account, I will encourage them to proactively do something about it. And for that, I would recommend that they try to establish a connection with the people who are actually developing the technology by attending talks, by watching talks, by going to your community and seeing who is around and who’s developing the technology around you. Those people will most likely be the people who you can establish that connection with on a more local level, and who will therefore try to do something inside your community. I think that that’s my strongest advice.

That’s great advice. Thank you so much for speaking with me today!

Takeaways

So, what can we learn from this interview?

Takeaway #1: Teaching and learning about data and technology, or anything at all, is best done by removing language barriers. To ensure that everyone has good data skills and is clued up on relevant technologies, it is important that conversations in the field are, when they can be, accessible and comprehendible to the general public.

Takeaway #2: Learning is best done through a process of asking questions and seeking answers, whether that be through reading papers, asking experts, or carrying out experiments and analysing data. It is a process of trial and error. We learn best by trying things out, which is best done when there is a clear end goal which we have set for ourselves.

Takeaway #3: Everyone has or should have a part in the development of technology, so we should all embrace our role in that process. How far we want to take that role is up to each of us, but we should not hold back from joining the conversation if we feel we have something to say.

Thanks to Dani for taking the time to speak to Taught By Humans and for sharing such valuable advice and insight. If this interview with Dani has been useful or of interest to you, look out for his short and sweet videos which will be announced later this week, and take a look at the rest of our interview series, all available on the Thoughts By Humans blog!